Decline in Prescriptions by NonMBBS Physicians


In India, where healthcare access varies greatly across regions, Non-MBBS physicians — medical practitioners without formal allopathic degrees — play a crucial role, especially in rural and low-income urban areas. These practitioners heavily rely on pharmaceutical detailing for drug information, making any shift in detailing practices by companies particularly impactful on their prescription behaviors. As pharmaceutical firms prioritize detailing for more profitable, unregulated drugs amidst declining margins from regulated molecules, there is a notable decline in prescriptions of regulated drugs by Non-MBBS physicians.

Non-MBBS Physicians: Role and Prevalence

Non-MBBS physicians are often the primary healthcare providers in India’s remote rural areas and urban slums, enjoying significant trust among these communities. Despite lacking formal medical qualifications, many prescribe allopathic medicines, filling a critical gap in healthcare access. In a survey by the Indian Medical Association, around 150,000 Non-MBBS physicians were identified in the state of Andhra Pradesh, with the country level estimates running at close to 2.5 million according to Association of Medical Consultants (Rao and Rao 2017). Some of these physicians specialize in ayurvedic or homeopathic medicine, but prescribe allopathic medicines; and a recent report by World Health Organization claims that 57.3% of allopathic doctors did not have a medical qualification (Anand and Fan 2016). A study by Center for Policy Research (CPR) reports that 68% of doctors in rural areas (1,519 villages surveyed) do not have any formal medical training (Sharma 2020). The WHO study (which reports that 57.3% of allopathic doctors have no qualification) and CP report together indicate the presence of allopathic doctors without formal medical degrees across India, but more concentrated in rural areas.

Data and Results

Our analysis utilizes data on the percentage of prescriptions issued by Non-MBBS physicians (NonMBBSRx%) from May 2009 to June 2014, focusing on 51 regulated molecules that represent a significant portion of pharmaceutical sales. We use an event study RDiT design to identify any discontinuities (with July 2013 as the cut-off), after accounting for flexible time trends. Descriptive measures and summary of results are presented below (we present the standardized effect sizes and fail-safe numbers as well following Hunter and Schmidt 2014; Rosenthal 1979).

Descriptive Measures

Sample size51
NonMBBBSRx%: Pre-regulation Mean (SD) .072(.059)
NonMBBBSRx%: Post-regulation Mean (SD).069(.061)

Note: Std. Dev. in parentheses

RDiT Results

LATE estimatea-.031(18)
Effect size-.142***
Fail-safe number633
Effect size-.296***
Fail-safe number831

*** p<.01, ** p<.05, * p<.1
Parentheses – No. of molecules with significant LATE estimates
(a) Average LATE of molecules with significant LATE (p<.05) values
(b) Meta-analysis – all molecules (significant and insignificant LATE estimates)
(c) Meta-analysis –molecules with significant LATE